The Evolving Thread Landscape PF Ai-Powered Cyberattacks:a Multi-Faceted Approach to Defense and Mitigate

EasyChair Preprint 14163

Abstract

The advent of artificial intelligence (AI) has revolutionized numerous industries, enhancing efficiency and innovation. However, this technological advancement also presents a double-edged sword, as cybercriminals increasingly leverage AI to orchestrate sophisticated cyberattacks (Goodfellow et al., 2018; Mühlbauer et al., 2022). This article explores the evolving threat landscape of AI-powered cyberattacks and proposes a multi-faceted approach to defense and mitigation. AI's capacity to analyze vast amounts of data, predict patterns, and learn autonomously makes it an invaluable tool for attackers (Cheng et al., 2021; Wang et al., 2022). These AI-driven threats range from automated phishing schemes and advanced malware to large-scale Distributed Denial of Service (DDoS) attacks, all characterized by their precision, adaptability, and ability to evade traditional cybersecurity measures (Cheng et al., 2020; Zhang et al., 2023). AI-powered cyberattacks pose significant risks across various sectors, including finance, healthcare, and government (Crosman, 2021; Zeng et al., 2022). The financial sector, for instance, faces AI-enhanced fraud detection evasion, while the healthcare industry is vulnerable to attacks on medical devices and patient data theft (Friedman, 2022; Borenstein et al., 2023).

Keyphrases: Artificial Intelligence (AI), Cyberattacks, sophisticated

@booklet{EasyChair:14163,
  author    = {Ralph Shad and Peter Broklyn and Axel Egon},
  title     = {The Evolving Thread Landscape PF Ai-Powered Cyberattacks:a Multi-Faceted Approach to Defense and Mitigate},
  howpublished = {EasyChair Preprint 14163},
  year      = {EasyChair, 2024}}